Remote sensing is a tool of interest for a large variety of applications. It is becoming
increasingly more useful with the growing amount of available remote sensing data …

The urban energy infrastructure is facing a rising number of challenges due to climate
change and rapid urbanization. In particular, the link between urban morphology and energy …

Integrating artificial intelligence with food category recognition has been a field of interest for
research for the past few decades. It is potentially one of the next steps in revolutionizing …

Based on the multi-source data (eg, building vector and remote sensing data) of the main
urban areas of Chongqing, China, this study selected a few natural factors—the relief …

Traditional target detection algorithms have difficulty to adapt complex environmental
changes and have limited applicable scenarios. However, the deep-learning-based target …

The spatial resolution of remote sensing images is becoming increasingly higher, posing
challenges in handling large very-high-resolution (VHR) remote sensing images for dense …

Semi-supervised learning (SSL) is a promising approach to reduce the labeling burden in
remote sensing scene classification tasks. However, most semi-supervised methods …

Amid global concerns regarding climate change and urbanization, understanding the
interplay between land use/land cover (LULC) changes, the urban heat island (UHI) effect …

Sustainable growth of resilient cities (RCs) requires equal development and monitoring of
natural and artificial ecosystems, such as biodiversity, transportation, building, legislation …

Despite the fact that urban agglomerations have undergone extensive ecological land
coverage modifications, exploration of the patterns and driving mechanisms associated with …